The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.
Multi-Agent Systems: A Survey
Open accessAbstract
Multi-agent systems (MASs) have received tremendous attention from scholars in different disciplines, including computer science and civil engineering, as a means to solve complex problems by subdividing them into smaller tasks. The individual tasks are allocated to autonomous entities, known as agents. Each agent decides on a proper action to solve the task using multiple inputs, e.g., history of actions, interactions with its neighboring agents, and its goal. The MAS has found multiple applications, including modeling complex systems, smart grids, and computer networks. Despite their wide applicability, there are still a number of challenges faced by MAS, including coordination between agents, security, and task allocation. This survey provides a comprehensive discussion of all aspects of MAS, starting from definitions, features, applications, challenges, and communications to evaluation. A classification on MAS applications and challenges is provided along with references for further studies. We expect this paper to serve as an insightful and comprehensive resource on the MAS for researchers and practitioners in the area.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Artificial intelligence: a modern approach
(1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 21,974
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788 · cited 2×
“ant colony, bees, fish, and penguins [38].”
BackgroundFlocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · Proceedings of the 14th annual conference on Computer graphics and interactive techniques · doi:10.1145/37401.37406 · Cited by 7,714
An Introduction to MultiAgent Systems
Wooldridge, M. (2002) · Cited by 5,394
Flocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · ACM SIGGRAPH Computer Graphics · doi:10.1145/37402.37406 · Cited by 5,148
Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory
Olfati-Saber, R. (2006) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.864190 · Cited by 5,037
Genetic Algorithms and Machine Learning
Goldberg, D. E., & Holland, J. H. (1988) · Machine Learning · doi:10.1023/a:1022602019183 · Cited by 3,193
Developing Multi‐Agent Systems with JADE
Bellifemine, F., Caire, G., & Greenwood, D. (2007) · Wiley eBooks · doi:10.1002/9780470058411 · Cited by 2,509
Genetic programming II: Automatic discovery of reusable programs
(1995) · Computers & Mathematics with Applications · doi:10.1016/0898-1221(95)90099-3 · Cited by 1,901
Laplacian matrices of graphs: a survey
Merris, R. (1994) · Linear Algebra and its Applications · doi:10.1016/0024-3795(94)90486-3 · Cited by 1,520
Research works printed but not linked: 51
- 10.1016/j.neucom.2015.02.058 · doi:10.1016/j.neucom.2015.02.058
- 10.1504/IJCIS.2009.029114 · doi:10.1504/ijcis.2009.029114
- 10.1016/j.amc.2013.12.020 · doi:10.1016/j.amc.2013.12.020
- kim, 2016, A realistic decision making for task allocation in heterogeneous multi-agent systems, Proc Journal of Computer Science, 94, 386, 10.1016/j.procs.2016.08.059 · doi:10.1016/j.procs.2016.08.059
- 10.1109/COMPSAC.2008.225 · doi:10.1109/compsac.2008.225
- 10.1109/CDC.2005.1582248 · doi:10.1109/cdc.2005.1582248
- 10.1007/978-3-642-40846-5_64 · doi:10.1007/978-3-642-40846-5_64
- 10.1016/j.jss.2015.02.039 · doi:10.1016/j.jss.2015.02.039
- 10.1103/PhysRev.127.276 · doi:10.1103/physrev.127.276
- ko?aczek, 2010, Social network analysis based approach to trust modeling for autonomous multi-agent systems, Agent and Multi-agent Technology for Internet and Enterprise Systems, 137, 10.1007/978-3-642-13526-2_7 · doi:10.1007/978-3-642-13526-2_7
- 10.1023/A:1024133006761 · doi:10.1023/a:1024133006761
- 10.1007/978-3-540-75254-7_24 · doi:10.1007/978-3-540-75254-7_24
- 10.1002/cpe.3760 · doi:10.1002/cpe.3760
- 10.1109/ICCKE.2014.6993399 · doi:10.1109/iccke.2014.6993399
- 10.1016/j.proeng.2012.06.018 · doi:10.1016/j.proeng.2012.06.018
- 2017, Sinalgo
- 2017, Ns2
- 2017, AnyLogic
- 2017, NetLogo
- 2017, MASON
- 2017, Repast
- 10.1109/IYCE.2013.6604142 · doi:10.1109/iyce.2013.6604142
- 2018, Gama
- juneja, 2015, A review of fipa standardized agent communication language and interaction protocols, J Netw Commun Emerg Technol, 5, 179
- 10.1002/asjc.1003 · doi:10.1002/asjc.1003
- 10.1145/1791212.1791215 · doi:10.1145/1791212.1791215
- wangapisit, 2014, Multi-agent systems modelling for evaluating joint delivery systems, Procedia-Soc Behav Sci, 125, 472, 10.1016/j.sbspro.2014.01.1489 · doi:10.1016/j.sbspro.2014.01.1489
- 10.1109/EUROCON.2015.7313688 · doi:10.1109/eurocon.2015.7313688
- davoodi, 2014, Simultaneous fault detection and consensus control design for a network of multi-agent systems, Proc Eur Control Conf (ECC), 575
- liu, 2016, Robust unknown input observer based fault detection for high-order multi-agent systems with disturbances, ISA Trans, 61, 15, 10.1016/j.isatra.2015.11.025 · doi:10.1016/j.isatra.2015.11.025
- 10.1016/j.trpro.2016.02.069 · doi:10.1016/j.trpro.2016.02.069
- 10.1016/j.arcontrol.2009.08.003 · doi:10.1016/j.arcontrol.2009.08.003
- 10.1016/j.jfranklin.2015.09.022 · doi:10.1016/j.jfranklin.2015.09.022
- krothapalli, 2002, Distributed task allocation in multi-agent systems, Proc IIE Annu Conf, 1
- sarika, 2015, AgentTab: An agent based approach to detect tabnabbing attack, Proc Journal of Computer Science, 46, 574, 10.1016/j.procs.2015.02.094 · doi:10.1016/j.procs.2015.02.094
- 10.1109/ITNG.2012.18 · doi:10.1109/itng.2012.18
- 10.1007/s11276-016-1251-x · doi:10.1007/s11276-016-1251-x
- 10.1109/TAC.2015.2457112 · doi:10.1109/tac.2015.2457112
- 10.1109/SAI.2015.7237331 · doi:10.1109/sai.2015.7237331
- fallah, 2013, Distributed estimation and control for large population stochastic multi-agent systems with coupling in the measurements, Proc Eur Control Conf (ECC), 4353
- 10.1016/j.ins.2007.11.005 · doi:10.1016/j.ins.2007.11.005
- 10.1016/j.eswa.2013.01.048 · doi:10.1016/j.eswa.2013.01.048
- 10.1109/ICICIC.2007.334 · doi:10.1109/icicic.2007.334
- 10.1109/LCN.2010.5735673 · doi:10.1109/lcn.2010.5735673
- 10.1109/JAS.2015.7081651 · doi:10.1109/jas.2015.7081651
- 10.1016/j.automatica.2015.08.021 · doi:10.1016/j.automatica.2015.08.021
- godsil, 2013, Algebraic Graph Theory, 207
- 10.1109/ICECC.2011.6067811 · doi:10.1109/icecc.2011.6067811
- 10.1016/j.trpro.2015.09.080 · doi:10.1016/j.trpro.2015.09.080
- 10.1002/asjc.542 · doi:10.1002/asjc.542
- 10.1016/j.jfranklin.2015.04.008 · doi:10.1016/j.jfranklin.2015.04.008
Cited by
The Rise and Potential of Large Language Model Based Agents: A Survey
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., et al. (2023) · arXiv · doi:10.48550/arxiv.2309.07864 · Cited by 972
The rise and potential of large language model based agents: a survey
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., et al. (2025) · Science China Information Sciences · doi:10.1007/s11432-024-4222-0 · Cited by 970
A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges
McEnroe, P., Wang, S., & Liyanage, M. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3176400 · Cited by 482
AI Agents and Agentic AI–navigating a plethora of concepts for future manufacturing
Ren, Y., Liu, Y., Ji, T., & Xu, X. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.08.017 · Cited by 66
A collective AI via lifelong learning and sharing at the edge
Soltoggio, A., Ben-Iwhiwhu, E., Braverman, V., Eaton, E., Epstein, B., Ge, Y., Halperin, L., How, J., Itti, L., Jacobs, M. A., et al. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00800-2 · Cited by 51
Metadata
- Authors
- Dorri, A., Kanhere, S. S., & Jurdak, R.
- Venue
- IEEE Access
- Published
- 2018
- Volume
- 6
- Pages
- 28573-28593
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2799899844
- Cited by
- 1,043
- References
- 118
- FWCI
- 30.27
- Type
- journal article
- Language
- en
- Open access
- gold
- Funders
- Data61 Ph.D. Scholarship
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Multi-Agent Systems: A Survey. https://app.cochat.ai/papers/10.1109/access.2018.2831228
- The paper
- Dorri, A., Kanhere, S. S., & Jurdak, R. (2018). Multi-Agent Systems: A Survey. IEEE Access. https://doi.org/10.1109/access.2018.2831228
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.